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Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems
Feng, Zhao1; Ling, Jie2; Wan, Feng1; Yang, Zhi Xin3
2021-05-14
Conference Name2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)
Source PublicationProceedings of 2021 IEEE 10th Data Driven Control and Learning Systems Conference, DDCLS 2021
Pages778-783
Conference Date14-16 May 2021
Conference PlaceSuzhou, China
CountryChina
Author of SourceSun M., Zhang H.
PublisherInstitute of Electrical and Electronics Engineers Inc.
Abstract

The rapid development and applications of precision motion systems pose a great challenge on tracking performance improvement to complete various industrial or scientific tasks. In this paper, an iterative learning enhanced integral terminal sliding mode control (IL- ITSMC) is developed to further enhance the performance of such systems under repetitive trajectory and disturbance. For the generally used second-order model in precision motion systems, an integral terminal sliding surface is utilized to improve the steady-state performance and robustness to unexpected disturbance. A novel reaching law is also designed to realize the finite-time convergence of the sliding surface. In addition, an iterative learning law is proposed based on the sliding surface to compensate the repetitive term through updating the feedforward control input iteratively. The stability in time domain and convergence in iterative domain are proven theoretically based on the well-known Lyapunov theory, respectively. The simulation results on a pizeo-actuated stage with hysteresis nonlinearity demonstrate that the proposed IL-ITSMC achieves the best tracking performance through comparisons, and the convergence speed is improved significantly in comparison with ITSMC with traditional P-type ILC (PIL- ITSMC) for a 10Hz sinusoidal repetitive trajectory.

KeywordPrecision Motion Tracking Sliding Mode Control Iterative Learning Control
DOI10.1109/DDCLS52934.2021.9455576
URLView the original
Indexed ByEI
Language英語English
Scopus ID2-s2.0-85114204185
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Affiliation1.Department of Electrical and Computer Engineering, University of Macau, Macao, P. R. China
2.College of Mechanical Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
3.State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering, University of Macau, Macao, P. R. China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Feng, Zhao,Ling, Jie,Wan, Feng,et al. Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems[C]. Sun M., Zhang H.:Institute of Electrical and Electronics Engineers Inc., 2021, 778-783.
APA Feng, Zhao., Ling, Jie., Wan, Feng., & Yang, Zhi Xin (2021). Iterative Learning enhanced Integral Terminal Sliding Mode Control for Precision Motion Systems. Proceedings of 2021 IEEE 10th Data Driven Control and Learning Systems Conference, DDCLS 2021, 778-783.
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